Overview

Dataset statistics

Number of variables7
Number of observations143
Missing cells11
Missing cells (%)1.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.6 KiB
Average record size in memory61.9 B

Variable types

Categorical1
DateTime1
Numeric5

Dataset

Description교차로의 방향별 교통 통행량(2022.5.~2023.3.)을 제공합니다. 데이터는 교차로명, 수집년월, 동,서,남,북,교통량 합계로 구성되어 있습니다.
URLhttps://www.data.go.kr/data/15113448/fileData.do

Alerts

동 is highly overall correlated with 교차로명High correlation
서 is highly overall correlated with 남 and 2 other fieldsHigh correlation
남 is highly overall correlated with 서 and 2 other fieldsHigh correlation
북 is highly overall correlated with 교차로명High correlation
교통량 합계 is highly overall correlated with 서 and 1 other fieldsHigh correlation
교차로명 is highly overall correlated with 동 and 3 other fieldsHigh correlation
남 has 11 (7.7%) missing valuesMissing
동 has unique valuesUnique
서 has unique valuesUnique
교통량 합계 has unique valuesUnique
북 has 2 (1.4%) zerosZeros

Reproduction

Analysis started2023-12-12 07:09:57.906454
Analysis finished2023-12-12 07:10:01.262975
Duration3.36 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

교차로명
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
가람교차로
11 
국책연구단지
11 
너래교차로
11 
새샘교차로
11 
성금사거리
11 
Other values (8)
88 

Length

Max length8
Median length5
Mean length5.6153846
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row가람교차로
2nd row가람교차로
3rd row가람교차로
4th row가람교차로
5th row가람교차로

Common Values

ValueCountFrequency (%)
가람교차로 11
 
7.7%
국책연구단지 11
 
7.7%
너래교차로 11
 
7.7%
새샘교차로 11
 
7.7%
성금사거리 11
 
7.7%
세종교차로 11
 
7.7%
어진교차로 11
 
7.7%
오송로교차로 11
 
7.7%
은하수교차로 11
 
7.7%
종합운동장교차로 11
 
7.7%
Other values (3) 33
23.1%

Length

2023-12-12T16:10:01.368204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
가람교차로 11
 
7.7%
국책연구단지 11
 
7.7%
너래교차로 11
 
7.7%
새샘교차로 11
 
7.7%
성금사거리 11
 
7.7%
세종교차로 11
 
7.7%
어진교차로 11
 
7.7%
오송로교차로 11
 
7.7%
은하수교차로 11
 
7.7%
종합운동장교차로 11
 
7.7%
Other values (3) 33
23.1%

수집년월
Date

Distinct11
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
Minimum2022-05-01 00:00:00
Maximum2023-03-01 00:00:00
2023-12-12T16:10:01.502558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:10:01.616234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)

동
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct143
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean230207.29
Minimum58419
Maximum584469
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T16:10:01.761278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum58419
5-th percentile76252.7
Q1114721.5
median232244
Q3299823
95-th percentile508213.8
Maximum584469
Range526050
Interquartile range (IQR)185101.5

Descriptive statistics

Standard deviation125542.58
Coefficient of variation (CV)0.5453458
Kurtosis0.34504115
Mean230207.29
Median Absolute Deviation (MAD)100870
Skewness0.74282347
Sum32919643
Variance1.576094 × 1010
MonotonicityNot monotonic
2023-12-12T16:10:01.947042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
251934 1
 
0.7%
238017 1
 
0.7%
216547 1
 
0.7%
347441 1
 
0.7%
321561 1
 
0.7%
180780 1
 
0.7%
287302 1
 
0.7%
289232 1
 
0.7%
333114 1
 
0.7%
232439 1
 
0.7%
Other values (133) 133
93.0%
ValueCountFrequency (%)
58419 1
0.7%
69548 1
0.7%
70804 1
0.7%
71232 1
0.7%
75518 1
0.7%
75902 1
0.7%
76065 1
0.7%
76252 1
0.7%
76259 1
0.7%
76465 1
0.7%
ValueCountFrequency (%)
584469 1
0.7%
562441 1
0.7%
562169 1
0.7%
555694 1
0.7%
542029 1
0.7%
525611 1
0.7%
516248 1
0.7%
510109 1
0.7%
491157 1
0.7%
488212 1
0.7%

서
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct143
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean246239.92
Minimum856
Maximum535177
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T16:10:02.141727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum856
5-th percentile109481.9
Q1138733
median235501
Q3333893
95-th percentile450030.6
Maximum535177
Range534321
Interquartile range (IQR)195160

Descriptive statistics

Standard deviation118273.49
Coefficient of variation (CV)0.4803181
Kurtosis-0.62360025
Mean246239.92
Median Absolute Deviation (MAD)98589
Skewness0.53510987
Sum35212308
Variance1.3988618 × 1010
MonotonicityNot monotonic
2023-12-12T16:10:02.325773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
172013 1
 
0.7%
160764 1
 
0.7%
450618 1
 
0.7%
477076 1
 
0.7%
438179 1
 
0.7%
385783 1
 
0.7%
380595 1
 
0.7%
385273 1
 
0.7%
444744 1
 
0.7%
350324 1
 
0.7%
Other values (133) 133
93.0%
ValueCountFrequency (%)
856 1
0.7%
102170 1
0.7%
103492 1
0.7%
104885 1
0.7%
105575 1
0.7%
105746 1
0.7%
108863 1
0.7%
109469 1
0.7%
109598 1
0.7%
110096 1
0.7%
ValueCountFrequency (%)
535177 1
0.7%
516923 1
0.7%
515797 1
0.7%
515635 1
0.7%
511424 1
0.7%
486680 1
0.7%
477076 1
0.7%
450618 1
0.7%
444744 1
0.7%
443451 1
0.7%

남
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct132
Distinct (%)100.0%
Missing11
Missing (%)7.7%
Infinite0
Infinite (%)0.0%
Mean357848.17
Minimum0
Maximum681863
Zeros1
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T16:10:02.510106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile172867.55
Q1263480.5
median335205
Q3479754
95-th percentile605973.75
Maximum681863
Range681863
Interquartile range (IQR)216273.5

Descriptive statistics

Standard deviation141976.32
Coefficient of variation (CV)0.39675016
Kurtosis-0.17180791
Mean357848.17
Median Absolute Deviation (MAD)78889.5
Skewness0.25281419
Sum47235958
Variance2.0157275 × 1010
MonotonicityNot monotonic
2023-12-12T16:10:02.678581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
283240 1
 
0.7%
568192 1
 
0.7%
510962 1
 
0.7%
528562 1
 
0.7%
548528 1
 
0.7%
551510 1
 
0.7%
544643 1
 
0.7%
511692 1
 
0.7%
553287 1
 
0.7%
520341 1
 
0.7%
Other values (122) 122
85.3%
(Missing) 11
 
7.7%
ValueCountFrequency (%)
0 1
0.7%
920 1
0.7%
16389 1
0.7%
140117 1
0.7%
165181 1
0.7%
165388 1
0.7%
172559 1
0.7%
173120 1
0.7%
174371 1
0.7%
177303 1
0.7%
ValueCountFrequency (%)
681863 1
0.7%
675035 1
0.7%
662507 1
0.7%
642229 1
0.7%
635974 1
0.7%
634037 1
0.7%
612813 1
0.7%
600378 1
0.7%
599962 1
0.7%
591776 1
0.7%

북
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct142
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean292014.85
Minimum0
Maximum474301
Zeros2
Zeros (%)1.4%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T16:10:02.871477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2476
Q1224295
median307992
Q3391989
95-th percentile450008.5
Maximum474301
Range474301
Interquartile range (IQR)167694

Descriptive statistics

Standard deviation120565.73
Coefficient of variation (CV)0.41287533
Kurtosis0.2043563
Mean292014.85
Median Absolute Deviation (MAD)84229
Skewness-0.78203904
Sum41758124
Variance1.4536095 × 1010
MonotonicityNot monotonic
2023-12-12T16:10:03.053560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2
 
1.4%
574 1
 
0.7%
264152 1
 
0.7%
83485 1
 
0.7%
82683 1
 
0.7%
2176 1
 
0.7%
1823 1
 
0.7%
2238 1
 
0.7%
2425 1
 
0.7%
2935 1
 
0.7%
Other values (132) 132
92.3%
ValueCountFrequency (%)
0 2
1.4%
574 1
0.7%
1823 1
0.7%
2097 1
0.7%
2176 1
0.7%
2238 1
0.7%
2425 1
0.7%
2935 1
0.7%
80167 1
0.7%
82683 1
0.7%
ValueCountFrequency (%)
474301 1
0.7%
468605 1
0.7%
457493 1
0.7%
451984 1
0.7%
451615 1
0.7%
451536 1
0.7%
450457 1
0.7%
450043 1
0.7%
449698 1
0.7%
449583 1
0.7%

교통량 합계
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct143
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1098783.4
Minimum171718
Maximum1603705
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T16:10:03.202693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum171718
5-th percentile616075.1
Q1933841
median1093131
Q31336925.5
95-th percentile1497202.4
Maximum1603705
Range1431987
Interquartile range (IQR)403084.5

Descriptive statistics

Standard deviation287916.81
Coefficient of variation (CV)0.26203235
Kurtosis0.42884657
Mean1098783.4
Median Absolute Deviation (MAD)190578
Skewness-0.62645941
Sum1.5712603 × 108
Variance8.2896087 × 1010
MonotonicityNot monotonic
2023-12-12T16:10:03.362547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
425441 1
 
0.7%
1004787 1
 
0.7%
1251757 1
 
0.7%
1416951 1
 
0.7%
1119946 1
 
0.7%
851626 1
 
0.7%
896509 1
 
0.7%
913769 1
 
0.7%
1080645 1
 
0.7%
1464720 1
 
0.7%
Other values (133) 133
93.0%
ValueCountFrequency (%)
171718 1
0.7%
213528 1
0.7%
318764 1
0.7%
425441 1
0.7%
577989 1
0.7%
585290 1
0.7%
598925 1
0.7%
615481 1
0.7%
621422 1
0.7%
628903 1
0.7%
ValueCountFrequency (%)
1603705 1
0.7%
1593189 1
0.7%
1569831 1
0.7%
1556231 1
0.7%
1555702 1
0.7%
1554343 1
0.7%
1542209 1
0.7%
1497306 1
0.7%
1496270 1
0.7%
1464720 1
0.7%

Interactions

2023-12-12T16:10:00.189275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:09:58.184451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:09:58.664371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:09:59.176450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:09:59.715784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:10:00.270189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:09:58.283543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:09:58.765339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:09:59.267143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:09:59.813076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:10:00.360814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:09:58.363392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:09:58.868487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:09:59.396514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:09:59.907216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:10:00.477620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:09:58.465894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:09:58.980654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:09:59.525666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:10:00.009353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:10:00.569741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:09:58.551497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:09:59.078393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:09:59.608952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:10:00.105582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T16:10:03.479631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
교차로명수집년월동서남북교통량 합계
교차로명1.0000.0000.8590.8970.8790.8850.763
수집년월0.0001.0000.0000.0000.0000.0000.131
동0.8590.0001.0000.6040.6720.7470.730
서0.8970.0000.6041.0000.8150.6830.799
남0.8790.0000.6720.8151.0000.6700.769
북0.8850.0000.7470.6830.6701.0000.786
교통량 합계0.7630.1310.7300.7990.7690.7861.000
2023-12-12T16:10:03.613846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
동서남북교통량 합계교차로명
동1.0000.207-0.020-0.0260.4490.581
서0.2071.0000.6180.1110.6340.629
남-0.0200.6181.0000.2150.7570.621
북-0.0260.1110.2151.0000.2980.630
교통량 합계0.4490.6340.7570.2981.0000.451
교차로명0.5810.6290.6210.6300.4511.000

Missing values

2023-12-12T16:10:01.056757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:10:01.208711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

교차로명수집년월동서남북교통량 합계
0가람교차로2022-05251934172013920574425441
1가람교차로2022-062380171607643577232482831004787
2가람교차로2022-072437951670053668422501691027811
3가람교차로2022-082417731623623624082471741013717
4가람교차로2022-092477531610823747962477351031366
5가람교차로2022-102501001620153826552534241048194
6가람교차로2022-11232244147292342386239297961219
7가람교차로2022-12228327144485334443239546946801
8가람교차로2023-01223512140980328222223008915722
9가람교차로2023-02213053135798312226217851878928
교차로명수집년월동서남북교통량 합계
133파란달교차로2022-063385751188532683003239931049721
134파란달교차로2022-073445291164472703123244591055747
135파란달교차로2022-083529291213172634703184171056133
136파란달교차로2022-093540391245022615913118461051978
137파란달교차로2022-103739921285502720493344481109039
138파란달교차로2022-113482311235892600343381791070033
139파란달교차로2022-123244531189432500413126331006070
140파란달교차로2023-01309008109598238946299498957050
141파란달교차로2023-02312053113816226859299734952462
142파란달교차로2023-033559931295612553353522421093131